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Using AberOWL for fast and scalable reasoning over BioPortal ontologies
BACKGROUND: Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide acce...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4976511/ https://www.ncbi.nlm.nih.gov/pubmed/27502585 http://dx.doi.org/10.1186/s13326-016-0090-0 |
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author | Slater, Luke Gkoutos, Georgios V. Schofield, Paul N. Hoehndorf, Robert |
author_facet | Slater, Luke Gkoutos, Georgios V. Schofield, Paul N. Hoehndorf, Robert |
author_sort | Slater, Luke |
collection | PubMed |
description | BACKGROUND: Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. METHODS: We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. RESULTS AND CONCLUSIONS: We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times. |
format | Online Article Text |
id | pubmed-4976511 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49765112016-08-09 Using AberOWL for fast and scalable reasoning over BioPortal ontologies Slater, Luke Gkoutos, Georgios V. Schofield, Paul N. Hoehndorf, Robert J Biomed Semantics Research BACKGROUND: Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. METHODS: We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. RESULTS AND CONCLUSIONS: We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times. BioMed Central 2016-08-08 /pmc/articles/PMC4976511/ /pubmed/27502585 http://dx.doi.org/10.1186/s13326-016-0090-0 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Slater, Luke Gkoutos, Georgios V. Schofield, Paul N. Hoehndorf, Robert Using AberOWL for fast and scalable reasoning over BioPortal ontologies |
title | Using AberOWL for fast and scalable reasoning over BioPortal ontologies |
title_full | Using AberOWL for fast and scalable reasoning over BioPortal ontologies |
title_fullStr | Using AberOWL for fast and scalable reasoning over BioPortal ontologies |
title_full_unstemmed | Using AberOWL for fast and scalable reasoning over BioPortal ontologies |
title_short | Using AberOWL for fast and scalable reasoning over BioPortal ontologies |
title_sort | using aberowl for fast and scalable reasoning over bioportal ontologies |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4976511/ https://www.ncbi.nlm.nih.gov/pubmed/27502585 http://dx.doi.org/10.1186/s13326-016-0090-0 |
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